Traffic Management and Traffic Engineering for the Future by Zlatka Avramova, Danny De Vleeschauwer, Kathleen Spaey,

By Zlatka Avramova, Danny De Vleeschauwer, Kathleen Spaey, Sabine Wittevrongel (auth.), Rui Valadas, Paulo Salvador (eds.)

This put up proeedings quantity encompasses a collection of learn contributions provided at FITraMEn 2008, held in the course of December 11-12, 2008 in Porto, Portugal.

The papers contained during this publication offer a common view of the continued study on site visitors administration and site visitors engineering within the Euro-NF community of Excellence, and provides a consultant instance of the issues at present investigated during this region, that spans issues reminiscent of bandwidth allocation and site visitors keep watch over, statistical research, site visitors engineering, and optical networks and video communications.

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Additional info for Traffic Management and Traffic Engineering for the Future Internet: First Euro-NF Workshop, FITraMEn 2008, Porto, Portugal, December 11-12, Revised Selected Papers

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We shall assume that the revenue earned per unit time on route r is proportional to the length of the route. Hence the revenue lost on route r is Rr = θr Lr /μr where θr = |Lr | θ (6) A Distributed Scheme for Value-Based Bandwidth Reconfiguration 25 Table 1. 0 where θ is the revenue earned per unit time on a single hop connection and |Lr | is the length in hops of route r. 007. Table 1 shows that the average lost revenue per 100,000 offered connections is reduced by a factor of 2 from 6,553 to 2,953.

For each OD pair we computed two paths. The first is simply the shortest path, we then prune the network of the links this path uses, and compute the second shortest path. Results for the us in this case can be seen in Fig. 7. This time, results of both UM and MATE are more similar, where the mean and quantile us are somewhat bigger for UM than MATE (although in some cases the difference easily exceeds 5%), and the minimum is relatively bigger for MATE than UM. However, the results of the comparison between UM and TeXCP are clearly in favor of the former.

We can see that while d1 is relatively small and the ABW is enough, source 1 uses only the lower path. 5, but always privileging better conditions on the upper path. 5 d1 Fig. 4. Some case-scenarios for the network in Fig. 2 The Benefits of Utility Maximization In this section we will assess the performance gain achieved by our proposal (UM from now on, as in Utility Maximization) over two well-known load-balancing techniques: MATE and TeXCP, which we already presented in Sec. 2. It is important to highlight that the results shown in this section were obtained by the distributed algorithm.

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